Leonid Kof Requirements Engineering Conference, RE '07.

Scenarios in industrial requirements documents are written as sequence of sentences in natural language The scenarios are often incomplete Some facts are so obvious that it is forgot to mention This approach analyzes textual scenarios with means of computational linguistics, indentifies where communicating objects or whole actions are missing

A message sequence chart (or MSC) is an interaction diagram from the SDL family very similar to UML's sequence diagram

Document authors introduce document defects Deletion: deletion reduces the world to the extent that we can handle In scenario: missing action subjects or objects or even in whole missing actions

1. The driver switches on the car (ignition key in position ignition on). 2. The instrument cluster is turned on and stays active.(either sender or receiver is missing) 3. After the trip the driver switches off the ignition. 4. The instrument cluster stays active for 30 seconds and then turns itself off. 5. The driver leaves the car.

A list of application specific names of potential communicating objects is useful. This paper uses ontology extraction from requirements document instead of a glossary Every sentence is parsed, the subject and the objects of every sentence are extracted. Each subject and each object is clustered according to grammatical context in which it occurs. Every pair of overlapping clusters is joined to a larger cluster, representing more general concepts. “is-a” relation (taxonomy) is derived from the cluster hierarchy. A non-taxonomic relation is assumed for every two concepts that often co-occur in the same sentence.

When translating a sentence to an MSC message, we decompose the sentence in three constituents: message sender, message content, message receiver. The message sender/receiver is the longest word sequence before/after the verb, contained in the ontology. The message content is the verb plus the word sequence between the verb and the first word of the message receiver, except for the determiners. If the receiver/ sender cannot be identified, the message content is the whole part of the sentence after/before the sender/receiver.

Indentifying the verb The sentence with POS-tags does not contain any verb tag The sentence with POS-tags contains more than one verb tag Modal verb, like “must” or “should”(rephrased) Passive, like “X is sent to Y by Z”(error case) Several subordinate sentences, like “If X sends Y to Z, Z sends …”(error case) Several actions, like “X sends Y to Z and replies something to T”(error case)

To indentify default senders and receivers, we organize the messages in a stack John enters the shop //push “enter” —Some actions in the shop— John leaves the shop //pop “enter” Identifying the Sender and Receiver in Incomplete Sentences

Identifying Missing Messages

The presented approach was evaluated on the instrument cluster specification, not used in a industrial development project Case study: The scenarios had to be rewritten The scenarios were translated to MSCs using the ontology(change) Repeat above using the corrected ontology

Adjust ontology The ontology branches containing non-hardware concepts (system messages, names of scale positions, sensor values (speed, temperature,... )) were deleted. The concepts “motor”, “sensor”, “wheel speed sensor”, “IC display”, “digital speedometer display”, “analog speedometer displays” were added to the branch “hardware” of the ontology.

It detects missing information in scenarios. It validates the previously extracted application specific ontology or glossary. It translates textual scenarios to MSCs.